95 citations · 172 across the 20 of their papers we have counts for
8 papers · 1 filter
Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models
Zhenyi Lu, Jie Tian, Wei Wei +4
Text classification is a crucial task encountered frequently in practical scenarios, yet it is still under-explored in the era of large language models (LLMs). This study shows tha…
Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue
Shixuan Fan, Wei Wei, Wendi Li +3
The core of the dialogue system is to generate relevant, informative, and human-like responses based on extensive dialogue history. Recently, dialogue generation domain has seen ma…
Personalized Topic Selection Model for Topic-Grounded Dialogue
Shixuan Fan, Wei Wei, Xiaofei Wen +3
Recently, the topic-grounded dialogue (TGD) system has become increasingly popular as its powerful capability to actively guide users to accomplish specific tasks through topic-gui…
Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognition
Zhuojun Ding, Wei Wei, Xiaoye Qu +1
Cross-lingual named entity recognition (NER) aims to train an NER model for the target language leveraging only labeled source language data and unlabeled target language data. Pri…
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
Chenghao Fan, Zhenyi Lu, Wei Wei +4
Efficient fine-tuning of large language models for task-specific applications is imperative, yet the vast number of parameters in these models makes their training increasingly cha…
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging
Zhenyi Lu, Chenghao Fan, Wei Wei +3
In the era of large language models, model merging is a promising way to combine multiple task-specific models into a single multitask model without extra training. However, two ch…
Reinforcement Learning with Token-level Feedback for Controllable Text Generation
Wendi Li, Wei Wei, Kaihe Xu +3
To meet the requirements of real-world applications, it is essential to control generations of large language models (LLMs). Prior research has tried to introduce reinforcement lea…
Joint Multi-Facts Reasoning Network For Complex Temporal Question Answering Over Knowledge Graph
Rikui Huang, Wei Wei, Xiaoye Qu +3
Temporal Knowledge Graph (TKG) is an extension of regular knowledge graph by attaching the time scope. Existing temporal knowledge graph question answering (TKGQA) models solely ap…